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| dify-agents | ||
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| , r.stdout) # Check if we can read wallets from the data directory directly - theyre | ||
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| AGENTS.md | ||
| alembic.ini | ||
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| CLEANUP.md | ||
| CODE_OF_CONDUCT.md | ||
| CODEOWNERS | ||
| CONTRIBUTING.md | ||
| DARKROOM_ADMIN_V2.md | ||
| databus_warm_cron.py | ||
| DESIGN.md | ||
| docker-compose.email.yml | ||
| Dockerfile | ||
| Dockerfile.worker | ||
| EMAIL_SETUP.md | ||
| generate_env.py | ||
| hf-model-card.md | ||
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| LICENSE | ||
| LICENSING_PRICING_STRATEGY.md | ||
| logo-preview.html | ||
| main.py | ||
| main.py.bak | ||
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| PORT_MAP.md | ||
| PRICING_ARCHITECTURE.md | ||
| PROPRIETARY_REGISTRATION.txt | ||
| pyproject.toml | ||
| pytest.ini | ||
| RAG_MODERNIZATION.md | ||
| RAG_R2_SETUP.md | ||
| README.md | ||
| README_HF.md | ||
| requirements.txt | ||
| rmi_langchain.py | ||
| rmi_sdk.py | ||
| RMI_SYSTEM_MAP.md | ||
| ruff.toml | ||
| safe_deploy.sh | ||
| SECURITY.md | ||
| SECURITY_STACK.md | ||
| smithery.yaml | ||
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| supabase_create_tables.sql | ||
| supabase_pgvector_setup.sql | ||
| test_new_scanners.py | ||
| uv.lock | ||
| worker.py | ||
| X402_ARCHITECTURE.md | ||
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| x402_tool_builder.py | ||
| X_AUDIT_AND_STRATEGY.md | ||
RMI — Rug Munch Intelligence
The first open-source crypto intelligence platform. Bloomberg-grade security and market intelligence for the on-chain world.
About Rug Munch Media LLC
We are Rug Munch Media LLC, a Wyoming-based software company building open-source tools that make the crypto economy safer — for consumers, builders, and institutions.
Crypto moves fast, and bad actors move faster. Phishing sites clone trusted brands within hours of a certificate being issued. Token launches rug in seconds. Wallets drain before a user knows what happened. The existing security stack is fragmented, expensive, and gated behind paywalls. We are building the open alternative.
RMI (Rug Munch Intelligence) is the first open-source crypto intelligence platform — a unified, AI-powered command center for token risk analysis, wallet forensics, multi-chain market data, phishing detection, and regulatory-grade intelligence. Our ambition is to become the Bloomberg terminal of crypto: one trusted surface where the entire industry can see what is happening, what is risky, and what is real.
Who we serve:
- Consumers — real-time protection against rug pulls, phishing, and wallet drainers
- Industry — exchanges, custodians, compliance teams, and researchers who need defensible on-chain intelligence
- AI agents — first-class Model Context Protocol (MCP) integration and x402 micropayments for autonomous tooling
We are an open-source company. Our code, our data, and our threat intelligence are public. Our business model is delivering the managed product, the API, and the institutional tier — not locking away the safety net.
What RMI does
Threat detection
- Token scanning — real-time rug-pull, honeypot, and scam detection across 18+ EVM chains + Solana
- Wallet forensics — track wallet behavior and transaction patterns, flag known bad actors
- Phishing detection — Certificate Transparency monitoring catches phishing domains within hours of registration, before they go live
- Bayesian reputation — statistically grounded deployer trust scoring, not vibes
Market intelligence
- 2,500+ assets — full coverage across major chains
- News aggregation — 1,800+ sources with clustering, dedup, and sentiment
- Whale alerts — large wallet movements and trading patterns in real time
- Multi-chain market data — OHLCV, liquidity, and volume from a single API
AI-native platform
- RAG-grounded reports — every claim cited, no hallucination
- MCP server — drop RMI into any AI agent or LLM workflow
- x402 micropayments — pay-per-call pricing for autonomous agents
- Open weights and open data — no vendor lock-in
Architecture
RMI is a single FastAPI backend with modular domain services:
Backend (FastAPI + Python)
├── DataBus — single data plane, 18 chains, 4-layer defense (labels → scanner → RAG → prices)
├── SENTINEL — multi-chain token security scanner
├── Wallet Bank — 39M+ labeled wallets, federated from open sources
├── RAG Engine — 3-pillar hybrid retrieval (dense + sparse + entity)
├── x402 Gateway — AI-agent micropayments
├── MCP Server — 221 tools for AI agents
└── Observability — Prometheus, GlitchTip, OpenTelemetry
Storage: PostgreSQL, Redis, Neo4j, Qdrant, ClickHouse, DuckDB.
Repositories
| Platform | URL |
|---|---|
| 🐙 GitHub (canonical) | https://github.com/Rug-Munch-Media-LLC/rugmuncher-backend |
| 🦊 GitLab (mirror) | https://gitlab.com/cryptorugmuncher/rugmuncher-backend |
| 🤗 HuggingFace (canonical) | https://huggingface.co/cryptorugmuncher/rugmuncher-backend |
Links
- 🌐 Website: https://rugmunch.io
- 📧 Contact: info@rugmunch.io
- 💬 Telegram: https://t.me/cryptorugmuncher
- 🐦 X / Twitter: https://x.com/cryptorugmunch
- 🐙 GitHub org: https://github.com/Rug-Munch-Media-LLC
- 🦊 GitLab: https://gitlab.com/cryptorugmuncher
- 🤗 HuggingFace org: https://huggingface.co/cryptorugmuncher
License
MIT — see LICENSE.md.
RMI is open source because the safety of the crypto economy cannot depend on a single vendor. We compete on the quality of the product, not on who is allowed to see the threat.
Built by Rug Munch Media LLC · Wyoming, USA
Open-source crypto intelligence. AI-native. Built to last.